I have 2 datasets with spatial data collected in the same area. One has information about 3000 trees. Their GPS locations and some measurements on each tree (height, surrounding vegetation and fruit abundance among others) The other data set is comprised of 68 data points of bird observations, spotted during systematic scanning of the area. From each observation I got the coordinates, date and time. What I would like to analyze is whether there is any predictive value in the distribution of trees in the area on the distribution of bird observations (i.e. are birds often seen near trees?). And then of course the follow-up question would be what aspect of a tree is the best predictor.
I have been trying some things in spatial data analysis using R (creating spatial weight matrices and trying to carry out spatial regression) but I keep hitting dead ends. Intuitively it feels like something that should be very doable but so far most methods I tried didn't work because of what my data is like.
Hence, here I am! Any tips? Every bit of help is highly appreciated!
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